Disturbances in movement coordination are the least well understood but often the most debilitating with respect to functional recovery following brain injury. These deficits in coordination are expressed in the form of abnormal muscle synergies and result in limited and stereotypic movement patterns that are functionally disabling. The result of these constraints in muscle synergies is an abnormal coupling between shoulder abduction and elbow flexion in the arm, which significantly reduces a stroke survivor's reaching space when he/she lifts up the weight of the impaired arm against gravity. Current neurotherapeutic approaches to mitigate these abnormal synergies have produced, at best, limited functional recovery.
In the leg the expression of abnormal synergies results in coupling between hip/knee extension with hip adduction. The result of this is a reduced ability of activating hip abductor muscles in the impaired leg during stance.
Disturbances of Voluntary Movement in Hemiparetic Stroke
A detailed qualitative description of the abnormal movement patterns in the impaired limb, and the natural history of the evolution of the various components of these abnormal clinical signs was first provided by Twitchell in 1951, in which he delineated both the major features of the movement disturbance, and the time course of recovery from stroke (Twitchell (1951) Brain 74: 443–480). A prominent feature of the disturbed movement patterns was the emergence of “stereotypic” movements, in which there appeared to be a relatively tight coupling of motion at adjacent joints in the upper and lower limbs.
Brunnstrom subsequently classified these abnormal stereotypic movement patterns into so called “synergies” which were broadly of either flexor or extensor type (Brunnstrom (1970) In: “Movement therapy in hemiplegia: a neurophysiological approach” Harper & Row, Publishers Inc., Hagerstown Md.). This qualitative classification of abnormal synergies, summarized in Table 1, has received limited modification or study by other investigators.
TABLE 1Upper Limb synergies in hemiparetic strokeafter Brunnstrom (1970, supra)Extension synergyFlexion synergyArmArmShoulder GirdleShoulder GirdleprotractionRetractionadductionabduction to 90°internal rotationexternal rotationElbowElbowextensionFlexionpronationSupinationLegLegHipHipextensionextensionadductionadductioninternal rotationinternal rotationKneeKneeextensionextension
Recent treatment approaches for hemiparetic upper extremity such as “motor relearning program”, electromyographic (EMG)-triggered/functional electrical stimulation, repeated mental practice, constraint-induced movement therapy, robot-aided sensory-motor training and bilateral arm training focus on task-specific repetition, increased intensity, and/or exercise in a real-world context. (See, for example, Langhammer and Stanghelle (2000) Clin. Rehabil. 14: 361–369; Cauraugh et al. (2000) Stroke 31: 1360–1364; Page et al. (2001) Phys. Ther. 81: 1455–1462; Miltner et al. (1999) Stroke 30: 586–592; van der Lee et al. (1999) Stroke 30: 2369–2375; Volpe et al. (2000) Neurology 54: 1938–1944; Volpe et al. (1999) Neurology 53: 1874–1876; Whitall et al. (2000) Stroke 31: 2390–2395; and Richards and Pohl (1999) Clin Geriatr Med 15: 819–832; Woldag and Hummelsheim (2002) J. Neurol. 249: 518–528) Despite favorable mounting evidence for the newer treatment models, none of the current neurorehabilitation techniques directly address the presence of abnormal synergistic patterns that constrain functional reaching (Dewald et al. (200 1) Topics in Stroke Rehabilitation 8: 1–11). Interventions that target abnormal synergistic movement patterns may ameliorate functional reaching and greatly benefit individuals with chronic stroke-induced movement discoordination.
In the lower limb recent findings from basic science provide preliminary evidence that functional locomotor recovery is possible after stroke or spinal cord injury when intense and accurate afferent input is provided in a task-specific and repetitive manner, Treadmill training is an example of a therapeutic modality that is derived from studies of adult cats with a low thoracic spinal transection who recovered the ability to step on a moving treadmill belt after they were trained on the treadmill and provided with truncal support, stimulation to recover extensor activity, and assistance in paw placement (Barbeau and Rossignol (1987) Brain Res. 412: 84–95; de Leon et al. (1998a) J. Neurophysiol. 80: 83–91; de Leon et al. (1998b) J. Neurophysiol. 79: 1329–1340; Lovely, et al., (1986) Exp. Neurol. 92: 421–435). Investigators have found that the spinal locomotor pools, which include a central pattern generator for automatic, alternating flexor and extensor leg muscle activity, are highly responsive to phasic segmental sensory inputs associated with walking and demonstrate evidence of learning during step training (Edgerton et al. (1997a) Adv Neurol. 72: 233–247; Edgerton et al. (1997b). Repetitive practice of the task was essential to the learning.
Barbeau and colleagues were the first investigators to translate this paradigm to human application for re-training walking after spinal cord injury and stroke (Barbeau et al., (1987) Brain Res. 437: 83–96; Finch et al. (1991) Phys. Ther. 71: 842–855; Visintin and Barbeau (1989) Can. J. Neurol. Sci. 16: 315–325; Visintin and Barbeau (1994) Paraplegia 32: 540–553). In their initial work, Barbeau et al. (Barbeau et al., (1987) supra) suspended the consumer over a treadmill using an overhead lift for body-weight support and clinician-provided assistance to the legs.
Task-specific training appears to be critical to the success of a locomotor training intervention post-stroke (Richards et al. (1993) Arch. Phys. Med. Rehabil. 74: 612–620). Treadmill training is a method of locomotor training that closely simulates the sensory elements specific to walking such as load on the lower extremities, upright trunk posture, proper lower limb kinematics, and normal walking speeds to generate effective lower limb stepping (Edgerton et al. (1997) supra; Behrman and Harkema (2000) Phys. Ther. 80: 688–700).
Within the past 10 years, there have been many studies that have specifically investigated the effects of treadmill training with or without body weight support (BWS) on post-stroke locomotor recovery. Treadmill training (with or without BWS) appears to be more effective than conventional therapy alone in locomotor recovery after stroke (Richards et al. (1993) supra; Hesse et al. (1995a) Stroke 26: 976–981; Hesse et al. (1995b); Laufer et al. (2001) J. Rehabil. Res. Dev. 38: 69–78; Pohl (2002) Stroke 33: 553–558; Sullivan et al. (2002) Arch. Phys. Med. Rehabil. 83: 683–691). While there is building evidence that this therapeutic modality may be beneficial in improving locomotor ability after stroke, there is little agreement or systematic study of the optimal training parameters to maximize functional outcomes (Tuszynski, Edgerton, and Dobkin (1999) J. Spinal Cord Med. 22: 143). None of the current studies have incorporated abnormal muscle coactivation patterns and associated joint toques in the lower extremity. We have quantitative evidence that abnormal coupling between hip and knee extension and hip adduction exists. Furthermore, we have preliminary data that this abnormal coupling reduces the ability to generate hip abduction while stading on the paretic leg. This results then in the inability to keep the pelvis horizontal and could result in the stroke subject falling towards the affected side. As in the case of the arm, interventions that target abnormal synergistic movement patterns may ameliorate balance and greatly benefit individuals with chronic stroke-induced movement discoordination.
Implementation of current treatment philosophies is more dependent on the therapist's background and training rather than clear clinical indications or objective and quantitative measures. Furthermore, there is no consensus in the literature to support one approach over the other or even a gold standard objective measure of their effectiveness in increasing functional recovery. Heinemann et al. reported on the relationship between functional status at discharge and intensities of therapies received during the patient's in-patient medical rehabilitation (Heinemann et al. (1995) Am. J. Phys. Med. Rehabil. 74: 315–326). The results for a group of 140 patients with traumatic brain injury (TBI) identified no significant correlation between functional outcome and the intensity of therapies. The apparent lack of benefit related to intensity of therapies may be due to such factors as spontaneous recovery, lack of adequate level of intensity based on the stroke patient's absolute tolerance, and most importantly, to inadequate measurement tools, which are subjective and non-quantitative, and do not possess the discrimination power required to detect meaningful functional change. Furthermore, most current approaches may not be effective in promoting the use of more functional elbow-shoulder torque combinations because of the implementation of limited, poorly controlled exercise sequences. None of the current neurorehabilitation techniques encourage movements outside abnormal synergic patterns in a rigorous and quantifiable way.
Evidence for Motor Learning and Strength Training Capabilities Following Stroke
We have evidence from previous work that, depending on the lesion location, hemiparetic stroke subjects are able to adapt to novel force perturbations applied to their impaired arms during reaching and retrieval movements (see Krebs et al. (1996) 18th Annual Conference of IEEE-EMBS; Raasch et al. (1997) Society for Neuroscience Abstracts 23). These findings demonstrate that a considerable level of motor learning capability persists in relation to the impaired arm. We also have evidence that chronic stroke subjects are able to use the residual motor learning capability to partially regain functional elbow/shoulder torque combinations (for example, shoulder abduction/external rotation combined with elbow extension) during an eight-week training protocol (see Ellis et al. (2002a) Program No. 169.2 Abstract Viewer/Itinerary Planner. Washington, D.C.: Society for Neuroscience Abstracts; Ellis et al. (2002b) Neurology Report 26: 191, Abstract; and Ellis et al. (2003) Program No. 714 Abstract Viewer/Itinerary Planner. Washington, D.C.: Society for Neuroscience Abstracts).
The Use of Robotics in Stroke-rehabilitation
At present, very little technology exists to support the recovery phase of stroke rehabilitation. However, there has been a surge of academic research on this topic in recent years (see, for example, Proceedings of the ICORR International Conference on Rehabilitation Robotics, 2001 and 2005). Of the academic research in progress, most research centers have elected to attempt to adapt or re-configure industrial robots for use in this application (Lum et al. (1995) Arch. Phys. Med. Rehabil. 83: 952–959). While this appears to be a reasonable approach it suffers from a critical drawback: twenty years of experience with industrial robots has shown that low impedance comparable to the human arm cannot be achieved with these machines. Because of their electromechanical design and control architecture, commercial robots are intrinsically position-controlled machines that do not yield easily under the action of external forces. Active force feedback can be used to enhance robot responsiveness but it is not sufficient to produce the “back-drivability” (low mechanical impedance) required to move smoothly and rapidly in compliance with a patient's actions (Lawrence (1988) Proc. IEEE Int. Conf. Robotics & Automation 1185–1191).
In contrast to commercial robotic technology, the MIT-MANUS robotic device was specifically designed for clinical neurological applications (Hogan et al. (1995) J. Interactive Robotic Therapist). The MIT-MANUS robotic device is configured for safe, stable and compliant operation in close physical contact with humans. Its computer impedance control (synonymous with position control) system modulates the way the robot reacts to mechanical perturbation from a patient or clinician and ensures a gentle compliant behavior (technically, a low and controllable impedance) (Hogan (1985) ASME J. Dynamic Systems Measurement and Control 107: 1–24). Operationally, a low impedance means that the robot can “get out of the way” as needed. However, due to the impedance control system, there is a moderate level of resistance due to inertia that the user must overcome to produce movement. This attribute limits the applicability of the MIT-MANUS to subjects who are able to exert enough force to overcome the inertial resistance of the device.
To test the feasibility of robot-aided neuro-rehabilitation, MIT investigators have used the MIT-MANUS robotic device in pilot studies on a daily basis for over seven years with CVA (cerebral vasculary incidence resulting in a stroke), Parkinson's disease, multiple sclerosis, spinal cord injury, amyotrophic lateral sclerosis (ALS), and Guillain-Barré (GB) patients at the Burke Rehabilitation Hospital. The key research objective in these pilot studies was to validate the concept of robot-aided exercise therapy and assess whether: (a) robot-aided therapy had adverse effects, (b) patients would tolerate the procedure, and (c) manipulation of the impaired limb influenced motor recovery. The results in these pilot clinical trials with 96 stroke patients showed that robot-aided neuro-rehabilitation did not impede recovery or exacerbate joint or tendon pain, and no adverse events occurred in an estimated 2000 hours of operation involving close contact with patients. A questionnaire administered during the bi-weekly standard assessment by the therapists showed that robot-assisted therapy was well accepted and tolerated by the patients. Most important, results indicated that patients in the experimental group improved further and faster, outranking the control group in the clinical assessments of the motor impairment involving shoulder and elbow. (See, for example, Aisen et al. (1997) Arch. Neurol. 54: 443–446; Krebs et al. (1998) IEEE Transact. Rehab. Engineer. 6: 75–87; Krebs et al. (2000) VA J. Rehab. Res. Dev. 37: 639–652; Volpe et al. (2001) Curr. Opin. Neurol. 14: 745–752; Volpe et al. (2000) Neurology 54: 1938–1944, and Ibid. (1999) Neurology 53: 1874–1876). However, a shortcoming of the MIT-MANUS obviating its usefulness for application in the evaluation and rehabilitation of gravity-induced discoordination is that it only works in a horizontal plane unable to provide various levels of limb support or operate in all directions of movement. In addition, impedance control technology must use a very light structure which may contain mechanical shortcomings such as friction or mechanical compliance. Even though forces may be measured at the patient interface, no compensation can be made for such non-linearities since they occur between the force control device, the motor, and the patient introducing errors that cannot be compensated.
Several similar US Patents have been issued to the above technology. For example, U.S. Pat. No. 5,466,213 to Hogan et al. is directed to an interactive robotic therapist that guides a patient's limb along a desired path through a desired series of exercises. The robotic therapist incorporates sensors that provide position, velocity, and force information at the patient's hand. The reference, however, does not teach using-force and position information in both real and virtual environments to measure, treat, or self-rehabilitate impaired movement performance.
U.S. Pat. No. 5,421,798 to Bond et al. is directed to an apparatus for evaluation of a limb of a test subject. The distal end of the limb is secured to the apparatus. The test subject moves the limb along a linear track. At least two components of the forces generated by the limb against the track are sensed. The force components are used to calculate the forces applied at each limb joint contributing to movement. The reference, however, does not teach using force and position information in both real and virtual environments to measure, treat, or self-rehabilitate impaired movement performance.
U.S. Pat. No. 5,830,160 to Reinkensmeyer is directed to a movement guiding system for quantifying, diagnosing, and treating impaired movement performance. The guiding system guides movement of a limb along a linear path and can quantify movement performance by measurting constrqaint forces generated during the movement. The reference does not teach force and position information in both real and virtual environments to measure, treat, or self-rehabilitate impaired movement performance.
U.S. Pat. No. 6,413,190 to Wood and Koval is directed to a rehabilitation apparatus and method that monitors patient rehabilitation thaearapy activity, the apparatus detecting sequential muscle contractions thereby operating a computer game that reflects the movement upon a screen. The patient is therefore encouraged to ensure that two muscles move in a temporal sequence to “play” the game. The reference does not teach using force and position information in both real and virtual environments to measure, treat, or self-rehabilitate impaired movement performance.
U.S. Pat. No. 4,936,299 to Erlandson discloses a rehabilitation apparatus having a robotic arm controlled by application software and a control board of a CPU. The patent also discloses a viewing screen and that the rehabilitation is initiated and under direction of a therapist. The reference does not teach using force and position information in both real and virtual environments to measure, treat, or self-rehabilitate impaired movement performance.
U.S. Pat. No. 6,613,000 to Reinkensmeyer discloses a system providing arm movement therapy for patients with sensory motor impairments having a joystick controlled by application software of a CPU over the World Wide Web using client-side applets. The patent also discloses a viewing screen and that the rehabilitation is performed without the direction or supervision of a therapist but in response to a predetermined desired therapeutic exercise. The reference does not teach using force and position information in both real and virtual environments to measure, treat, or self-rehabilitate impaired movement performance.
Admittance control technology uses a force measurement device (loadcell) placed at the patient interface. The loadcell functions as the force feedback device in a closed loop force control system. Therefore the forces are always controlled at the patient's interface, and system non-linearities mentioned before are minimized because they occur inside the force control loop and can therefore be compensated to a large degree.
A commercial robot that uses admittance control is the HAPTICMASTER (HM) from FCS Control Systems. The FCS Control Systems' control technology originated and was patented in the late 1970s in the field of flight training and simulation to generate aircraft control forces for the pilot. It has matured over the years from a patented to a company proprietary technology. See U.S. Pat. No. 4,398,889, herein incorporated by reference in its entirety.
The HAPTICMASTER, which was designed with rehabilitation applications in mind, has low inertia such that the user doesn't feel much resistance when attempting to move the device. The low level inertial properties of the HM enable application to individuals with all levels of impairment severity including individuals with severe impairment who would otherwise be unable to move against the inertial resistance of other robotic devices. Work done at the University of Reading, England has shown that the robot is safe and can assist reaching movements to various targets in the workspace of the paretic arm following stroke (Coote and Stokes (2003) Technol. Disabil. 15: 27–34; Harwin and Hillman (2003) Robotica 21; Marinncek et al (2001) Association for the Advancement of Assistive Technology in Europe AAATE '01. Amsterdam; Washington, D.C.: IOS Press,). However, it has been employed to assist subjects in reaching movements with the upper extremity constantly supported by an external device.
Each of the robotic devices described above demonstrate the ability to use robotics as a device for implementing therapeutic training post-stroke. In addition, each of these devices is capable of measuring motion and tracking progress during training. With this current patent, we propose to generate virtual mechanical/visual environments that can simulate weightlessness or make the body or limb progressively heavier to beyond its actual weight. Using these realistic simulated environments generated by a combination of multi degree of freedom robotics and visual feedback we can measure the effect of abnormal joint torque coupling in the upper and lower extremities as well as train individuals to slowly relearn to deal with the weight of their limb or body while reaching (arm) or walking (leg).
Virtual Reality
Haptics is the science of applying tactile or force sensation to human interaction with computers. A haptic device is one that involves physical contact between the computer and the-user, usually through an input/output device, such as a joystick or data gloves, that senses the body's movements. By using haptic devices, the user can not only feed information to the computer but can receive information from the computer in the form of a felt sensation on some part of the body. This is referred to as a haptic interface. For example, in a virtual reality environment, a user can pick up a virtual tennis ball using a data glove. The computer senses the movement and moves the virtual ball on the display. However, because of the nature of a haptic interface, the user will feel the tennis ball in his hand through tactile sensations that the computer sends through the data glove, mimicking the feel of the tennis ball in the user's hand. Typical uses a haptic interface are disclosed in U.S. Pat. No. 6,636,161 (Rosenberg, issued Oct. 21, 2003) and U.S. Pat. No. 6,697,043 (Shahoian, issued Feb. 24, 2004).